title: Evidence synthesis for decision making 1: introduction.
abstract: We introduce the series of 7 tutorial papers on evidence synthesis methods for decision making, based on the Technical Support Documents in Evidence Synthesis prepared for the National Institute for Health and Clinical Excellence (NICE) Decision Support Unit. Although oriented to NICE's Technology Appraisal process, which examines new pharmaceutical products in a cost-effectiveness framework, the methods presented throughout the tutorials are equally relevant to clinical guideline development and to comparisons between medical devices, or public health interventions. Detailed guidance is given on how to use the other tutorials in the series, which propose a single evidence synthesis framework that covers fixed and random effects models, pairwise meta-analysis, indirect comparisons, and network meta-analysis, and where outcomes expressed in several different reporting formats can be analyzed without recourse to normal approximations. We describe the principles of evidence synthesis required by the 2008 revision of the NICE Guide to the Methods of Technology Appraisal and explain how the approach proposed in these tutorials was designed to conform to those requirements. We finish with some suggestions on how to present the evidence, the synthesis methods, and the results.
authors.affiliation: School of Social and Community Medicine, University of Bristol, Bristol, UK (SD, NJW, AEA)
authors.forename: Sofia
authors.initials: S
authors.lastname: Dias
authors.affiliation: School of Social and Community Medicine, University of Bristol, Bristol, UK (SD, NJW, AEA)
authors.forename: Nicky J
authors.initials: NJ
authors.lastname: Welton
authors.affiliation: Department of Health Sciences, University of Leicester, Leicester, UK (AJS)
authors.forename: Alex J
authors.initials: AJ
authors.lastname: Sutton
authors.affiliation: School of Social and Community Medicine, University of Bristol, Bristol, UK (SD, NJW, AEA)
authors.forename: A E
authors.initials: AE
authors.lastname: Ades
mesh_terms: D003657:Decision Making; D019317:Evidence-Based Medicine
keywords: Bayesian meta-analysis; cost-effectiveness analysis; systematic reviews